LATPC combines variance-based selection of refusal features for adversarial training with an inference-time embedding calibrator, reducing jailbreak success while curbing over-refusal across several LLMs.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks
LATPC combines variance-based selection of refusal features for adversarial training with an inference-time embedding calibrator, reducing jailbreak success while curbing over-refusal across several LLMs.